Revision as of 21:36, 25 May 2023 by Admin (Created page with "You are given the following results from a regression model. {| class="table table-bordered" ! Observation number (i) !! <math>y_i</math> !! <math>\hat{f}(x_i) </math> |- | 1...")
ABy Admin
May 25'23
Exercise
You are given the following results from a regression model.
| Observation number (i) | [math]y_i[/math] | [math]\hat{f}(x_i) [/math] |
|---|---|---|
| 1 | 2 | 4 |
| 2 | 5 | 3 |
| 3 | 6 | 9 |
| 4 | 8 | 3 |
| 5 | 4 | 6 |
Calculate the sum of squared errors (SSE).
- -35
- -5
- 5
- 35
- 46
Copyright 2023. The Society of Actuaries, Schaumburg, Illinois. Reproduced with permission.
ABy Admin
May 26'23
Key: E
Solution: SSE is sum of the squared differences between the observed and predicted values. That is,
[(2 − 4)2 + (5 − 3)2 + (6 − 9)2 + (8 − 3)2 + (4 − 6)2 ] = 46.
Copyright 2023. The Society of Actuaries, Schaumburg, Illinois. Reproduced with permission.